Hi Sean,
I can reproduce all the CPU issues, slowness, etc. if I try to import the
data that I have in milliseconds, specifying precision as milliseconds.

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If I insert the same data without specifying any precision and query
without specifying any precision, the database is lightingly fast. The same
data.
The reason I was adding precision=ms is that I thought it was the right
thing to do. The manual advises that Influx sores the data in nanoseconds
but to use the lowest precision to insert. So at some stage I even used
hours, but inserted the data with precision=h. When Influx tried to convert
that data to nanoseconds, index, etc, then it was having a hissy fit.
Is it a bug or the manual should state that if you query the data at the
same precision as you insert, then you can go with the lowest precision and
do not specify what precision you are inserting?
Thanks,
Tanya
On 13 October 2016 at 10:26, Tanya Unterberger <tanya.unterber...@gmail.com>
wrote:
> Hi Sean,
>
> The data is from 1838 to 2016, daily (sparse at times). We need to retain
> it, therefore the default policy.
>
> Thanks,
> Tanya
>
> On 13 October 2016 at 06:26, Sean Beckett <s...@influxdb.com> wrote:
>
>> Tanya, what range of time does your data cover? What are the retention
>> policies on the database?
>>
>> On Tue, Oct 11, 2016 at 11:14 PM, Tanya Unterberger <
>> tanya.unterber...@gmail.com> wrote:
>>
>>> Hi Sean,
>>>
>>> 1. Initially I killed the process
>>> 2. At some point I restarted influxdb service
>>> 3. Error logs show no errors
>>> 4. I rebuilt the server, installed the latest rpm. Reimported the data
>>> via scripts. Data goes in, but the server is unusable. Looks like indexing
>>> might be stuffed. The size of the data in that database is 38M. Total size
>>> of /var/lib/influxdb/data/ 273M
>>> 5. CPU went beserk and doesn't come down
>>> 6. A query like select count(blah) to the measurement that was batch
>>> inserted (10k records at a time) is unusable and times out
>>> 7. I need to import around 15 million records. How should I throttle
>>> that?
>>>
>>> At the moment I am pulling my hair out (not a pretty sight)
>>>
>>> Thanks a lot!
>>> Tanya
>>>
>>> On 12 October 2016 at 06:11, Sean Beckett <s...@influxdb.com> wrote:
>>>
>>>>
>>>>
>>>> On Tue, Oct 11, 2016 at 12:11 AM, <tanya.unterber...@gmail.com> wrote:
>>>>
>>>>> Hi,
>>>>>
>>>>> It seems that the old issue might have surfaced again (#3349) in v1.0.
>>>>>
>>>>> I tried to insert a large number of records (3913595) via a script,
>>>>> inserting 10000 rows at a time.
>>>>>
>>>>> After a while I received
>>>>>
>>>>> HTTP/1.1 500 Internal Server Error
>>>>> Content-Type: application/json
>>>>> Request-Id: ac8ebbbe-8f70-11e6-8ce7-000000000000
>>>>> X-Influxdb-Version: 1.0.0
>>>>> Date: Tue, 11 Oct 2016 05:12:02 GMT
>>>>> Content-Length: 20
>>>>>
>>>>> {"error":"timeout"}
>>>>> HTTP/1.1 100 Continue
>>>>>
>>>>> I killed the process, after which the whole box became pretty much
>>>>> unresponsive.
>>>>>
>>>>
>>>> Killed the InfluxDB process, or the batch writing script process?
>>>>
>>>>
>>>>>
>>>>> There is nothing in the logs (i.e. sudo ls /var/log/influxdb/ gives me
>>>>> nothing) although the setting for http logging is true:
>>>>>
>>>>
>>>> systemd OSes put the logs in a new place (yay!?). See
>>>> http://docs.influxdata.com/influxdb/v1.0/administration/logs/#systemd
>>>> for how to read the logs.
>>>>
>>>>
>>>>>
>>>>> [http]
>>>>> enabled = true
>>>>> bind-address = ":8086"
>>>>> auth-enabled = true
>>>>> log-enabled = true
>>>>>
>>>>> I tried to restart influx, but got the following error:
>>>>>
>>>>> Failed to connect to http://localhost:8086
>>>>> Please check your connection settings and ensure 'influxd' is running.
>>>>>
>>>>
>>>> The `influx` console is just a fancy wrapper on the API. That error
>>>> doesn't mean much except that the HTTP listener in InfluxDB is not yet up
>>>> and running.
>>>>
>>>>
>>>>>
>>>>> Although I can see that influxd is up an running:
>>>>>
>>>>> > systemctl | grep influx
>>>>> influxdb.service
>>>>> loaded active running InfluxDB is an open-source,
>>>>> distributed, time series database
>>>>>
>>>>> What do I do now?
>>>>>
>>>>
>>>> Check the logs as referenced above.
>>>>
>>>> The non-responsiveness on startup isn't surprising. It sounds like the
>>>> system was overwhelmed with writes, which means that the WAL would have
>>>> many points cached, waiting to be flushed to disk. On restart, InfluxDB
>>>> won't accept new writes or queries until the cached ones in the WAL have
>>>> persisted. For this reason, the HTTP listener is off until the WAL is
>>>> flushed.
>>>>
>>>>
>>>>>
>>>>> I tried the same import over the weekend, then the script timeout
>>>>> happened eventually but the result was the same unresponsive, unusable
>>>>> server. We rebuilt the box and started again.
>>>>>
>>>>
>>>> It sounds like the box is just overwhelmed. Did you get backoff
>>>> messages from the writes before the crash? What are the machine specs?
>>>>
>>>>
>>>>
>>>>>
>>>>> Perhaps it is worthwhile mentioning that the same measurement already
>>>>> contained about 9 million records. Some of these records had the same
>>>>> timestamp as the ones I tried to import, i.e. they should have been
>>>>> merged.
>>>>>
>>>>
>>>> Overwriting points is much much more expensive than posting new points.
>>>> Each overwritten point triggers a tombstone record which must later be
>>>> processed. This can trigger frequent compactions of the TSM files. With a
>>>> high write load and frequent compactions, the system would encounter
>>>> significant CPU pressure.
>>>>
>>>>
>>>>>
>>>>> Interestingly enough the same amount of data was fine when I forgot to
>>>>> add precision in ms, i.e. all records were imported as nanoseconds, but in
>>>>> fact they "lacked" 6 zeroes.
>>>>>
>>>>
>>>> That would mean all points are going to the same shard. It is more
>>>> resource intensive to load points across a wide range of time, since more
>>>> shard files are involved. InfluxDB does best with sequential
>>>> chronologically ordered unique points from the very recent past. The more
>>>> the write operation differs from that, the lower the throughput.
>>>>
>>>>
>>>>>
>>>>> Please advise what kind of action I can take.
>>>>>
>>>>
>>>> Look in the logs for errors. Throttle the writes. Don't overwrite more
>>>> points than you have to.
>>>>
>>>>
>>>>>
>>>>> Thanks a lot!
>>>>> Tanya
>>>>>
>>>>> --
>>>>> Remember to include the InfluxDB version number with all issue reports
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>>>>
>>>>
>>>>
>>>> --
>>>> Sean Beckett
>>>> Director of Support and Professional Services
>>>> InfluxDB
>>>>
>>>> --
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>>>
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>>
>>
>>
>> --
>> Sean Beckett
>> Director of Support and Professional Services
>> InfluxDB
>>
>> --
>> Remember to include the version number!
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>
>
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